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Secure, Context-Aware and QoS-Enabled SDN Architecture to Improve Energy Efficiency in IoT-Based Smart Buildings

  • Conference paper
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Distributed Computing for Emerging Smart Networks (DiCES-N 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1348))

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Abstract

Nowadays, buildings are increasingly energy intensive, as they represent almost 40% of total energy consumption and more than 35% of CO2 emissions. The excessive and unnecessary use of planet resources and the use fossil fuel and a non-renewable energy source urged government and industry to explore new research directions and utility-driven energy improvement programs to drive advances in energy-efficient. Energy efficiency in smart buildings can be achieved by introducing a context-aware Internet of Things (IoT) approach, where sensors can learn from their surrounding environment to control the actuators in a coordinated network. However, the IoT network requirements are constantly changing in unpredictable fashion, which needs faster and frequent on-demand network reconfiguration. Software Defined Network (SDN) has been envisioned as a new approach to enable a flexible and agile network programmability in diverse IoT scenarios. However, the focus has primarily been on the design of the SDN computation logic, i.e. controllers, while the dynamic delivery and operations service-inferred IoT resource allocation has been postponed.

To address this plethora of challenges, this paper we first extend Software Defined Network (SDN) with Network Function Virtualization (NFV) to support distributed IoT sensing devices automation and orchestration in micro-grid data center at the network edge of smart campus building. Second, we introduce a novel IoT data management model based on data-centric middleware IoT message broker that implements a hierarchical containment tree for retrieving sensor data from remote IoT devices. Then, we introduce a context-aware knowledge learning approach that maps raw sensing data into a meaningful context and transform them into the appropriate context representation models. Finally, we provide a proof of concept to demonstrate successful deployment and provisioning of virtualized services in the context of Smart Campus research project.

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Acknowledgments

This work was partially funded by the Tunisian Ministry of Higher Education and Scientific Research (MES) under the Young Researchers Incentive Program (19PEJC09-04) and the CV Raman research program 2017675. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of MES or CV Raman program.

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Authors and Affiliations

  1. SYSCOM ENIT, ISSAT Mateur, University of Carthage, Tunis, Tunisia

    Akram Hakiri & Bassem Sallemi

  2. Faculty of Sciences, Department of Computer Sciences, University of Tunis El Manar, Tunis, Tunisia

    Bassem Sallemi & Sadok Ben Yahia

  3. Planning Department, Tunisie Telecom, Les jardins du Lac II, 1073, Tunis, Tunisia

    Fatma Ghandour

  4. Tallinn University of Technology, Akadeemia tee 15a, Tallinn, Estonia

    Sadok Ben Yahia

Authors
  1. Akram Hakiri
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  2. Bassem Sallemi
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  3. Fatma Ghandour
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  4. Sadok Ben Yahia
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Corresponding author

Correspondence to Akram Hakiri .

Editor information

Editors and Affiliations

  1. University of Carthage, Zarzouna Bizerte, Tunisia

    Imen Jemili

  2. Bordeaux INP, France Talence, France

    Mohamed Mosbah

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Hakiri, A., Sallemi, B., Ghandour, F., Ben Yahia, S. (2020). Secure, Context-Aware and QoS-Enabled SDN Architecture to Improve Energy Efficiency in IoT-Based Smart Buildings. In: Jemili, I., Mosbah, M. (eds) Distributed Computing for Emerging Smart Networks. DiCES-N 2020. Communications in Computer and Information Science, vol 1348. Springer, Cham. https://doi.org/10.1007/978-3-030-65810-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-65810-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65809-0

  • Online ISBN: 978-3-030-65810-6

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